that would be not cool. luckily that does not in fact happen

Samuel 24 Jun 2024

introducing @kiki-bouba.mozzius.dev like the labeller to find out if you're kiki or bouba (wip, still working out the prompt)

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ǝuuɐſ 25 Jun 2024

every time a user clicks that button the lights flicker a little, a faint whirring can be heard, and the seas run dry, the fish are screaming samuel. they are screaming your name

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Samuel

@samuel.fm

that would be not cool. luckily that does not in fact happen

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ddouglas 💎 🇺🇦 🦋 25 Jun 2024

Are you sure? 👻👻👻

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ǝuuɐſ 25 Jun 2024

I heard the fish myself

Certified Robot Enjoyer 26 Jun 2024

Funny, that's not what the actual engineers who know what they're talking about say. Are the engineers liars,, Samuel? oecd.ai/en/wonk/how-...

Scope-1 onsite water consumption: AI servers’ massive energy consumption generates much heat. To dissipate the heat into the outside environment and avoid server overheating, data centres commonly use cooling towers and/or outside air, which need a staggering amount of clean, fresh water. Cooling towers rely on water evaporation to produce cold water, and outside air needs water for evaporation assistance when it’s too hot and for humidity control when it’s too dry. Because of the high power densities of AI servers, on-chip liquid cooling may be employed: closed-loop circulating liquid directly moves the heat from the servers to the data centre facility (e.g., the facility’s cooling water loop). Then, the heat moved to the facility will be rejected by cooling towers or outside air, which consumes water.

Scope-2 offsite water consumption: Generating electricity also consumes a lot of water through cooling at thermal power and nuclear plants and expedited water evaporation caused by hydropower plants. Thus, AI is responsible for scope-2 offsite water consumption.

The scope-1 and scope-2 water consumption are sometimes collectively called operational water consumption. There is also scope-3 embodied water consumption for AI supply chains. For example, to produce a microchip takes approximately 2,200 gallons of Ultra-Pure Water (UPW). That aside, training a large language model like GPT-3 can consume millions of litres of fresh water, and running GPT-3 inference for 10-50 queries consumes 500 millilitres of water, depending on when and where the model is hosted. GPT-4, the model currently used by ChatGPT, reportedly has a much larger size and hence likely consumes more water than GPT-3.

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Certified Robot Enjoyer 26 Jun 2024

Your little toy sucks up and wastes potable water by the bottle, Samuel. Pouring a whole bottle of water out on the dirt would be less harmful.